SOTAVerified

Music Source Separation

Music source separation is the task of decomposing music into its constitutive components, e. g., yielding separated stems for the vocals, bass, and drums.

( Image credit: SigSep )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 107 papers

TitleStatusHype
Hybrid Transformers for Music Source SeparationCode5
The Whole Is Greater than the Sum of Its Parts: Improving Music Source Separation by Bridging NetworkCode4
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech SeparationCode3
Training-Free Multi-Step Audio Source SeparationCode2
A Stem-Agnostic Single-Decoder System for Music Source Separation Beyond Four StemsCode2
SCNet: Sparse Compression Network for Music Source SeparationCode2
Pre-training Music Classification Models via Music Source SeparationCode2
Music Source Separation Based on a Lightweight Deep Learning Framework (DTTNET: DUAL-PATH TFC-TDF UNET)Code2
The Sound Demixing Challenge 2023 x2013 Music Demixing TrackCode2
All for One and One for All: Improving Music Separation by Bridging NetworksCode2
Music Source RestorationCode1
SynthSOD: Developing an Heterogeneous Dataset for Orchestra Music Source SeparationCode1
A fully differentiable model for unsupervised singing voice separationCode1
Sound Demixing Challenge 2023 Music Demixing Track Technical Report: TFC-TDF-UNet v3Code1
Quantifying Spatial Audio Quality ImpairmentCode1
MedleyVox: An Evaluation Dataset for Multiple Singing Voices SeparationCode1
An Efficient Short-Time Discrete Cosine Transform and Attentive MultiResUNet Framework for Music Source SeparationCode1
Music Mixing Style Transfer: A Contrastive Learning Approach to Disentangle Audio EffectsCode1
Music Source Separation with Band-split RNNCode1
Music Source Separation with Generative FlowCode1
VocaLiST: An Audio-Visual Synchronisation Model for Lips and VoicesCode1
Unsupervised Music Source Separation Using Differentiable Parametric Source ModelsCode1
CWS-PResUNet: Music Source Separation with Channel-wise Subband Phase-aware ResUNetCode1
Danna-Sep: Unite to separate them allCode1
Transfer Learning with Jukebox for Music Source SeparationCode1
KUIELab-MDX-Net: A Two-Stream Neural Network for Music DemixingCode1
Unsupervised Source Separation via Bayesian Inference in the Latent DomainCode1
Music Demixing Challenge 2021Code1
A Unified Model for Zero-shot Music Source Separation, Transcription and SynthesisCode1
Multi-Task Audio Source SeparationCode1
A cappella: Audio-visual Singing Voice SeparationCode1
LaSAFT: Latent Source Attentive Frequency Transformation for Conditioned Source SeparationCode1
Mixing-Specific Data Augmentation Techniques for Improved Blind Violin/Piano Source SeparationCode1
Multi-channel U-Net for Music Source SeparationCode1
Unsupervised Interpretable Representation Learning for Singing Voice SeparationCode1
Meta-learning Extractors for Music Source SeparationCode1
Time-Domain Audio Source Separation Based on Wave-U-Net Combined with Discrete Wavelet TransformCode1
Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained ModelsCode1
End-to-end music source separation: is it possible in the waveform domain?Code1
Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source SeparationCode1
Is MixIT Really Unsuitable for Correlated Sources? Exploring MixIT for Unsupervised Pre-training in Music Source Separation—0
Solving Copyright Infringement on Short Video Platforms: Novel Datasets and an Audio Restoration Deep Learning Pipeline—0
Score-informed Music Source Separation: Improving Synthetic-to-real Generalization in Classical MusicCode0
Separate This, and All of these Things Around It: Music Source Separation via Hyperellipsoidal Queries—0
Sanidha: A Studio Quality Multi-Modal Dataset for Carnatic Music—0
MAJL: A Model-Agnostic Joint Learning Framework for Music Source Separation and Pitch Estimation—0
Learned Compression for Compressed LearningCode0
Music Foundation Model as Generic Booster for Music Downstream Tasks—0
Task-Aware Unified Source Separation—0
An Ensemble Approach to Music Source Separation: A Comparative Analysis of Conventional and Hierarchical Stem Separation—0
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All datasetsMUSDB18MUSDB18-HQSlakh2100

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Sparse HT Demucs (fine tuned)SDR (avg)9.2—Unverified
2Hybrid Transformer Demucs (f.t.)SDR (avg)9—Unverified
3Band-Split RNN (semi-sup.)SDR (avg)8.97—Unverified
4TFC-TDF-UNet (v3)SDR (avg)8.34—Unverified
5Band-Split RNNSDR (avg)8.23—Unverified
6Hybrid DemucsSDR (avg)7.72—Unverified
7KUIELab-MDX-NetSDR (avg)7.54—Unverified
8CDE-HTCNSDR (avg)6.89—Unverified
9Attentive-MultiResUNetSDR (avg)6.81—Unverified
10DEMUCS (extra)SDR (avg)6.79—Unverified
#ModelMetricClaimedVerifiedStatus
1BS-RoFormer (L=12, OA)SDR (avg)11.99—Unverified
2BS-RoFormer (L=6, OA)SDR (avg)9.8—Unverified
3SCNet-largeSDR (avg)9.69—Unverified
4Sparse HT Demucs (fine tuned)SDR (avg)9.2—Unverified
5Hybrid Transformer Demucs (f.t.)SDR (avg)9—Unverified
6SCNetSDR (avg)9—Unverified
7Band-Split RNN (semi-sup.)SDR (avg)8.97—Unverified
8TFC-TDF-UNet (v3)SDR (avg)8.34—Unverified
9Band-Split RNNSDR (avg)8.24—Unverified
10Dual-Path TFC-TDF UNet (DTTNet)SDR (avg)8.15—Unverified
#ModelMetricClaimedVerifiedStatus
1DiCoSe (Deterministic)SI-SDRi (Bass)20.04—Unverified
2LQ-VAE + Scalable TransformerSDR (bass)7.42—Unverified